This paper investigates whether using natural logarithms (logs) of price indices for forecasting
inflation rates is preferable to employing the original series. Univariate forecasts for annual inflation
rates for a number of European countries and the USA based on monthly seasonal consumer price
indices are considered. Stochastic seasonality and deterministic seasonality models are used. In many
cases the forecasts based on the original variables result in substantially smaller root mean squared
errors than models based on logs. In turn, if forecasts based on logs are superior, the gains are
typically small. This outcome sheds doubt on the common practice in the academic literature to
forecast inflation rates based on differences of logs.